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Diastolic dysfunction and HFpEF

TL;DR — Hypertension is a major HFpEF substrate, but neither diastolic dysfunction nor HFpEF is synonymous with HHD. The transition involves ventricular and arterial stiffening, impaired relaxation, fibrosis, microvascular dysfunction, chronotropic and vascular reserve failure, atrial remodeling and comorbid obesity/CKD/AF (Paulus 2013, PMID 23684677; Redfield 2023, PMID 36917048). Resting echocardiography may miss exertional elevation of filling pressure; intermediate diagnostic scores require exercise echo or invasive hemodynamics rather than label inflation (Reddy 2018, PMID 29792299; Pieske 2019, PMID 31504452). SGLT2 inhibitors reduce HF worsening/hospitalization across EF above 40%, but trial populations were HF syndromes, not uniformly adjudicated HHD (Anker 2021, PMID 34449189; Solomon 2022, PMID 36027570). The prevention gap is identifying and treating the reversible pre-HF stage.

1. The continuum—and its breaks

Stage Typical findings What is not yet established
Pressure exposure only Hypertension; normal cardiac phenotype Who will remodel
Subclinical remodeling LVH, concentric remodeling, impaired GLS, LA change Best screening interval
Diastolic dysfunction Abnormal relaxation or filling-pressure indices Whether a single resting abnormality predicts HF transition
Pre-HF with biomarkers Structural disease plus troponin/NP signal Biomarker-triggered treatment benefit
Clinical HFpEF Symptoms/signs plus objective elevated filling pressure, EF usually ≥50% Etiologic fraction attributable to hypertension
Mixed/late failure AF, pulmonary hypertension, RV disease, renal congestion, possible EF decline Reversibility of each component

The continuum is a useful map, not a guaranteed sequence. HFpEF cohorts contain normal, concentric and eccentric LV geometry; concentric LVH is common but not universal (Shah 2013, PMID 24097113). Contemporary synthesis also treats LVH and fibrosis as interacting but separable HFpEF substrates rather than one obligatory stage sequence (Peikert 2026, PMID 40892534).

2. Relaxation, compliance and filling pressure

Diastolic filling depends on active myocardial relaxation, passive chamber stiffness, restoring forces, atrial function, rhythm, pericardial restraint and loading conditions. Hypertension can affect all of them through hypertrophy, fibrosis and vascular coupling (Gallo 2024, PMID 38928371; González 2024, PMID 38084597).

Mechanism Measurement signal Important confounder
Slower relaxation Reduced e′, prolonged relaxation Age, ischemia, heart rate
Higher filling pressure E/e′, TR velocity, LA volume, natriuretic peptide Rhythm, obesity, valve disease
Increased chamber stiffness Pressure–volume relation Requires invasive or modeled assessment
Loss of atrial reservoir/conduit function LA strain and volume AF and mitral disease
Arterial stiffening Pulse pressure, PWV Age and CKD
Limited reserve Exercise filling pressure, output, chronotropic response Deconditioning and lung disease

3. Diastolic dysfunction is not clinical HF

In a community cohort of 283 asymptomatic, nonischemic hypertensive adults, 35 (12.3%) met contemporary LV diastolic-dysfunction criteria. Over 5.4 years, MACE occurred in 26.6% with baseline dysfunction versus 9.9% with normal diastolic function; adjusted HR was 2.5 (95% CI 1.20–5.25) (Zhou 2022, PMID 35698035).

This shows prognostic enrichment, not equivalence to HFpEF. HF requires a clinical syndrome and objective evidence of cardiac dysfunction or elevated filling pressure; isolated grade-I relaxation abnormality is insufficient (Pieske 2019, PMID 31504452; Redfield 2023, PMID 36917048).

4. What changes at the HHD-to-HFpEF boundary?

A matched Baltimore study compared 37 HFpEF patients, 40 nonfailing hypertensive-LVH participants and 56 normotensive controls. Many abnormalities were shared between HFpEF and nonfailing LVH; HFpEF showed greater concentric LVH, estimated wedge pressure 20 versus 16 mm Hg, and distinct LA dilation/dysfunction (Melenovsky 2007, PMID 17222731).

The result is important because it resists a one-variable transition model: mass, vascular stiffness or diastolic indices alone poorly separated nonfailing HHD from HFpEF.

Domain Nonfailing hypertensive LVH HFpEF shift
LV geometry Often remodeled More severe but overlapping
Filling pressure May be elevated Higher at rest and/or exercise
Left atrium Load exposure may be present Dilation, stiffness and dysfunction more prominent
Vascular reserve Reduced Further impaired
Symptoms Absent or nonspecific Exertional dyspnea, congestion, fatigue
Right heart/pulmonary circulation Often preserved Pulmonary pressure and RV involvement may emerge

5. Left atrium as cumulative exposure record

The LA integrates chronic filling pressure and rhythm burden. Size, reservoir strain, conduit function and booster-pump function provide nonredundant information; AF both results from and worsens atrial remodeling (Beltrami 2018, PMID 29283475).

An integrated atrial assessment is preferable to LA volume alone because enlargement is late, rhythm-dependent and influenced by obesity and valve disease (Beltrami 2018, PMID 29283475; Melenovsky 2007, PMID 17222731).

6. Vascular and microvascular coupling

Arterial stiffness increases pulsatile afterload and impairs ventricular–arterial reserve, linking aging, hypertension, CKD and HFpEF (Kim 2024, PMID 38887204). In a 424-person general-population study, low digital reactive-hyperemia responders had higher adjusted odds of LVH (OR 2.60) and diastolic dysfunction (OR 2.66) than moderate/high responders (Cauwenberghs 2021, PMID 34569675).

The systemic-inflammation paradigm proposes that obesity, diabetes, lung disease and salt-sensitive hypertension drive coronary microvascular endothelial inflammation, reduced NO–cGMP–PKG signaling, hypertrophy and stiffness (Paulus 2013, PMID 23684677). Coronary microvascular dysfunction is documented across hypertrophy and HF phenotypes but is not specific to HHD (Camici 2020, PMID 31999329). The pathway is mechanistically influential but not a universally verified sequence.

7. Obese HFpEF is a distinct cluster

In invasive exercise phenotyping, 99 participants with obese HFpEF had greater plasma volume, concentric remodeling, RV dilation/dysfunction and epicardial fat than 96 nonobese HFpEF participants and 71 controls; they had lower natriuretic peptide despite greater hemodynamic burden (Obokata 2017, PMID 28381470).

This creates two practical interpretation errors:

  1. Normal or modest natriuretic peptide does not exclude HFpEF in obesity.
  2. Obesity is not merely a confounder to be indexed away; it may define a different hemodynamic phenotype.

TOPCAT latent-class analysis similarly identified three phenogroups: a younger lower-remodeling group, an older AF/LA/arterial-stiffness group, and an obesity/diabetes/CKD/concentric-LVH/inflammation group with the highest risk (Cohen 2020, PMID 31926856). Expert phenotype profiling proposes treatment alignment by dominant mechanism, but prospective interaction validation remains limited (Anker 2023, PMID 37461163).

8. Diagnostic scores

Tool Inputs Rule Proper use
H₂FPEF Obesity, AF, age >60, ≥2 antihypertensives, E/e′ >9, PASP >35 0–9; odds doubled per point in derivation/validation Estimate pretest probability in unexplained dyspnea
HFA-PEFF Pretest, echo morphology/function, natriuretic peptide ≥5 definite; ≤1 unlikely; 2–4 functional testing Stepwise consensus algorithm
Exercise echo E/e′, TR velocity and symptoms under stress Protocol-dependent Resolve exertional filling-pressure uncertainty
Invasive exercise hemodynamics PCWP and flow during exercise Reference adjudication in difficult dyspnea Specialist test, selection-sensitive

The H₂FPEF score was derived in 414 and tested in 100 referred patients; AUC was 0.841 and OR 1.98 (95% CI 1.74–2.30) per point (Reddy 2018, PMID 29792299). HFA-PEFF is consensus-based and explicitly routes intermediate scores to functional testing (Pieske 2019, PMID 31504452).

9. Treatment once HFpEF is established

Trial Population Primary result Safety/interpretation
EMPEROR-Preserved 5,988; EF >40% CV death/HF hospitalization HR 0.79 (95% CI 0.69–0.90) Benefit mainly HF hospitalization; more genital/urinary infection and hypotension (Anker 2021, PMID 34449189)
DELIVER 6,263; EF >40% Worsening HF/CV death HR 0.82 (0.73–0.92) CV-death HR 0.88 (0.74–1.05); benefit driven by worsening HF (Solomon 2022, PMID 36027570)
TOPCAT 3,445; EF ≥45% Primary composite HR 0.89 (0.77–1.04), P=0.14 HF hospitalization HR 0.83; hyperkalemia 18.7% vs 9.1% (Pitt 2014, PMID 24716680)
PARAGON-HF 4,822; EF ≥45% Total HF hospitalization/CV death rate ratio 0.87 (0.75–1.01), P=0.06 Overall primary endpoint not significant (Solomon 2019, PMID 31475794)

Across DELIVER and EMPEROR-Preserved (12,251 participants), SGLT2 inhibition reduced cardiovascular death or first HF hospitalization with HR 0.80 (95% CI 0.73–0.87) (Vaduganathan 2022, PMID 36041474).

These results apply to verified HF across an EF spectrum. They do not prove that treating asymptomatic imaging-defined HHD with an SGLT2 inhibitor prevents HFpEF.

BP control inside those same trials was itself measured. A participant-level pooled analysis of TOPCAT (Americas), PARAGON-HF, DELIVER and FINEARTS-HF (17,788 patients, mean age 72±9 years, 47% women, mean baseline systolic BP 129±15 mm Hg) defined time in target range (TIR) as the percentage of the first post-randomization year with systolic BP 110–<130 mm Hg, interpolated from standardized visit measurements. Median TIR was 38% (≈139 days). Randomization to active therapy raised TIR by 2% (95% CI −2 to 6) with spironolactone, 7% (5 to 9) with sacubitril/valsartan, 2% (0 to 4) with dapagliflozin and 3% (1 to 5) with finerenone. Higher TIR was associated with lower subsequent risk of HF hospitalization or cardiovascular death (P=0.021), driven by HF hospitalization (P=0.007); associations with cardiovascular and all-cause death were not significant, and stricter or more liberal ranges gave qualitatively similar results (Lu 2026, PMID 42669134).

This is a landmark-adjusted observational association within randomized trials, so it cannot separate BP control from the disease severity and adherence that produce it. Its value for HHD is narrower and real: it quantifies how little of the first HFpEF year is actually spent inside a guideline BP band, which bounds how much of any HFpEF drug effect can plausibly be attributed to pressure lowering.

10. Prevention versus treatment

REVERSE-LVH provides a bridge: in 78 participants with hypertension and CMR-LVH, sacubitril/valsartan reduced interstitial volume more than valsartan at similar ambulatory SBP and improved several secondary remodeling markers (Lee 2025, PMID 40739095). It did not test HF events.

The most consequential missing trial would enroll a reproducible pre-HF HHD phenotype, randomize treatment triggered by that phenotype, and measure incident HF rather than imaging change alone.

That design must retain HHD attribution rather than importing the whole HFpEF syndrome, whose multiorgan heterogeneity is the central reason phenotype-specific roadmaps were proposed (Shah 2016, PMID 27358439; Nwabuo 2020, PMID 32016791).

Open questions

  • Which combination of LA function, GLS, CMR fibrosis, exercise filling pressure and biomarkers best identifies near-term HFpEF transition? (Melenovsky 2007, PMID 17222731; Pieske 2019, PMID 31504452)
  • Can phenotype-targeted therapy outperform syndrome-wide HFpEF therapy? (Cohen 2020, PMID 31926856; Shah 2016, PMID 27358439)
  • Does treating microvascular dysfunction or arterial stiffness prevent clinical HF in hypertensive remodeling? (Paulus 2013, PMID 23684677; Kim 2024, PMID 38887204)
  • What outcome and threshold should define successful pre-HF intervention? (Zhou 2022, PMID 35698035; Lee 2025, PMID 40739095)
  • Does randomizing to a time-in-range BP strategy, rather than an office-visit target, change HF hospitalization in HFmrEF/HFpEF? (Lu 2026, PMID 42669134)

References

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